Mobile application management

ABSTRACT

Code of a particular application is analyzed against a semantic model of a software development kit of a particular platform. The semantic model associates a plurality of application behaviors with respective application programming interface (API) calls of the particular platform. A set of behaviors of the particular application is identified based on the analysis of the code and a particular one of the set of behaviors is identified as an undesired behavior. The particular application can be automatically modified to remediate the undesired behavior. The particular application can be assigned to one of a plurality of device modes, and access to the particular application on a user device can be based on which of the plurality of device modes is active on the user device.

TECHNICAL FIELD

This disclosure relates in general to the field of computer securityand, more particularly, to security of mobile devices.

BACKGROUND

The distribution and use of mobile devices, such as smart phones, PDAs,laptops, netbooks, and tablets have grown at a rapid pace. Further,adoption of such devices is also expanding and number overtaking that ofdesktop computers and feature phones in some developed markets. Thesophistication of the operating systems and the hardware capabilities ofmobile devices is also increasing and, in some cases, outpacing thefeatures sets and functionality of traditional computers. For example,modem mobile devices can possess such varied sensors and subsystems aslocation sensors like global positioning systems (GPS), accelerometers,gyroscopes, near field communication (NFC), etc. that are ordinarily notincluded on traditional devices. Adding to this the always connectednature of some mobile devices and the tendency for their owners toconstantly carry the devices, mobile devices have become attractivetargets for malware developers, hackers, and other malicious actors.Further, “app stores” and other open marketplaces have enabled thedevelopment of tens of thousands of applications (or “apps”) that havebeen developed for such devices, including device platforms such asGoogle Android™, iOS™, Windows™, etc., with some of these applicationsbeing of questionable quality and purpose.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified schematic diagram of an example system includingan application management system in accordance with one embodiment;

FIG. 2 is a simplified block diagram of an example system including anexample application manager and user device in accordance with oneembodiment;

FIG. 3 is a simplified block diagram representing analysis and healingof an application for a user device in accordance with one embodiment;

FIG. 4 is a simplified block diagram representing an example behavioralassessment of an application in accordance with one embodiment;

FIGS. 5A-5B are simplified representation of control flow within exampleapplications in accordance with some embodiments;

FIG. 6 is a simplified block diagram representing example subsystemsaccessible to an example user device in accordance with someembodiments;

FIG. 7 is a simplified block diagram representing use of rules todetermine application behaviors in accordance with some embodiments;

FIG. 8 is a simplified flow diagram representing assessment ofapplication behaviors and healing of undesired behaviors in accordancewith one embodiment;

FIG. 9 is a simplified flow diagram representing decisions made inconnection with the management and remediation of applicationsdetermined to include undesirable behaviors based on behavioral analysesof the applications in accordance with one embodiment;

FIG. 10 is a simplified flow diagram representing an example healing ofan application in accordance with one embodiment;

FIG. 11 is a simplified block diagram representing an example healing ofan application in accordance with one embodiment;

FIGS. 12A-12E represent examples of detection and remediation ofundesired behaviors of an application in accordance with someembodiments;

FIG. 13 is a simplified flow diagram representing an example healing ofan application in accordance with one embodiment;

FIGS. 14A-14B are simplified block diagram representing features of anexample mode manager in accordance with some embodiments;

FIGS. 15A-15B represent portions of example algorithms for managingmodes in a user device in accordance with some embodiments;

FIG. 16 is a simplified block diagram for sharing device modes betweendevices in accordance with one embodiment;

FIG. 17 is a simplified flow diagram illustrating use of context inmanaging modes of a device in accordance with one embodiment;

FIG. 18 is a simplified flow diagram illustrating remote provisioningand/or activation of modes on a user device in accordance with someembodiments;

FIG. 19 is a simplified block diagram representing applicationinformation collected in accordance with some embodiments;

FIGS. 20A-20D are screenshots of example user interfaces provided inconnection with mode management of a user device in accordance with someembodiments;

FIGS. 21A-21C are flowcharts representing example operations involvingan example application management system in accordance with someembodiments.

Like reference numbers and designations in the various drawings indicatelike elements.

DETAILED DESCRIPTION

FIG. 1 illustrates an example system 100 including, for instance, anexample application management server 105, and one or more mobile userdevices 110, 115, 120, 125, such as smart phones, mobile gaming systems,tablet computers, laptops, netbooks, among other examples. Applicationmanagement server 105 can provide one or more services to the userdevices to assist in the management of applications downloaded,installed, used, or otherwise provided for the user devices 110, 115,120, 125. User devices 110, 115, 120, 125 can access application servers140, such as centralized application storefronts, such as, for example,Android Market™, iTunes™, and other examples. Application servers 140can further include, in some examples, other sources of softwareapplications that can be downloaded and installed on user devices 110,115, 120, 125. User devices 110, 115, 120, 125 can communicate with andconsume the data and services of the application management server 105over one or more networks 130, including local area networks and widearea networks such as the Internet. Among the services of an exampleapplication management server 105, applications available to userdevices 110, 115, 120, 125 can be analyzed, assessed, and repaired atleast in part by functionality provided through application managementserver 105. Further, application management server 105, in connectionwith services made available to user devices 110, 115, 120, 125 caninteract with and consume resources, data, and services of other outsidesystems and servers such as information servers 145. For instance, suchinformation servers 145 can host services and data that provideadditional intelligence and context regarding applications available touser devices 110, 115, 120, 125, among other examples.

In general, “servers,” “clients,” “client devices,” “user devices,”“mobile devices,” “computing devices,” “network elements,” “hosts,”“system-type system entities,” and “systems,” including system devicesin example computing environment 100 (e.g., 105, 110, 115, 120, 125,140, 145, etc.), can include electronic computing devices operable toreceive, transmit, process, store, or manage data and informationassociated with the computing environment 100. As used in this document,the term “computer,” “processor,” “processor device,” or “processingdevice” is intended to encompass any suitable processing device. Forexample, elements shown as single devices within the computingenvironment 100 may be implemented using a plurality of computingdevices and processors, such as server pools including multiple servercomputers. Further, any, all, or some of the computing devices may beadapted to execute any operating system, including Linux™, UNIX™,Microsoft Windows™, Apple OS™, Apple iOS™, Google Android™, WindowsServer™, etc., as well as virtual machines adapted to virtualizeexecution of a particular operating system, including customized andproprietary operating systems.

Further, servers, user devices, network elements, systems, and othercomputing devices can each include one or more processors,computer-readable memory, and one or more interfaces, among otherfeatures and hardware. Servers can include any suitable softwarecomponent or module, or computing device(s) capable of hosting and/orserving software applications and services (e.g., personal safetysystems, services and applications of server 105, etc.), includingdistributed, enterprise, or cloud-based software applications, data, andservices. For instance, in some implementations, an applicationmanagement server 105, application servers 140, information servers 145,or other subsystems of computing system 100 can be comprised at least inpart by cloud-implemented systems configured to remotely host, serve, orotherwise manage data, software services and applications interfacing,coordinating with, dependent on, or otherwise used by other services anddevices in system 100. In some instances, a server, system, subsystem,or computing device can be implemented as some combination of devicesthat can be hosted on a common computing system, server, server pool, orcloud computing environment and share computing resources, includingshared memory, processors, and interfaces.

User, endpoint, or client computing devices (e.g., 110, 115, 120, 125,etc.) can include traditional and mobile computing devices, includingpersonal computers, laptop computers, tablet computers, smartphones,personal digital assistants, feature phones, handheld video gameconsoles, desktop computers, internet-enabled televisions, and otherdevices designed to interface with human users and capable ofcommunicating with other devices over one or more networks (e.g., 130).Computer-assisted, or “smart,” appliances can include household andindustrial devices and machines that include computer processors and arecontrolled, monitored, assisted, supplemented, or otherwise enhance thefunctionality of the devices by the computer processor, other hardware,and/or one or more software programs executed by the computer processor.Computer-assisted appliances can include a wide-variety ofcomputer-assisted machines and products including refrigerators, washingmachines, automobiles, HVAC systems, industrial machinery, ovens,security systems, and so on.

Attributes of user computing devices, computer-assisted appliances,servers, and computing devices generally, can vary widely from device todevice, including the respective operating systems and collections ofsoftware programs loaded, installed, executed, operated, or otherwiseaccessible to each device. For instance, computing devices can run,execute, have installed, or otherwise include various sets of programs,including various combinations of operating systems, applications,plug-ins, applets, virtual machines, machine images, drivers, executablefiles, and other software-based programs capable of being run, executed,or otherwise used by the respective devices.

Some system devices can further include at least one graphical displaydevice and user interfaces, supported by computer processors of thesystem devices, that allow a user to view and interact with graphicaluser interfaces of applications and other programs provided in system,including user interfaces and graphical representations of programsinteracting with applications hosted within the system devices as wellas graphical user interfaces associated with application managementserver services and other applications, etc. Moreover, while systemdevices may be described in terms of being used by one user, thisdisclosure contemplates that many users may use one computer or that oneuser may use multiple computers.

While FIG. 1 is described as containing or being associated with aplurality of elements, not all elements illustrated within computingenvironment 100 of FIG. 1 may be utilized in each alternativeimplementation of the present disclosure. Additionally, one or more ofthe elements described in connection with the examples of FIG. 1 may belocated external to computing environment 100, while in other instances,certain elements may be included within or as a portion of one or moreof the other described elements, as well as other elements not describedin the illustrated implementation. Further, certain elements illustratedin FIG. 1 may be combined with other components, as well as used foralternative or additional purposes in addition to those purposesdescribed herein.

Turning now to the example block diagram of FIG. 2, an example system isshown including an application manager 205, user system 210, among othercomputing devices and network elements including, for instance,application servers 140 and information servers 145 communicating overone or more networks 130. In one example implementation, applicationmanager 205 may include one or more processor devices 215, memoryelements 218, and one or more other software and/or hardware-implementedcomponents. For instance, in one example implementation, an applicationmanager 205 may include a share engine 220, user manager 222, healingengine 225, behavior analysis engine 228, application intelligenceengine 230, among other potential machine executable logic, componentsand functionality including combinations of the foregoing.

In one example, a share engine 220 can be configured to providefunctionality for managing crowdsourcing of information relating toapplications (e.g., made available by application servers 140), as wellas the sharing of such information and resources, including resourcesgenerated at least in part by or collected by application manager 205.For example, an example share engine 220 can allow modified applications232 developed for particular users and associated user devices (e.g.,210) as well as defined application modes 240 to be shared acrossmultiple user devices (e.g., 210), among other examples. An example usermanager 222 can provide functionality for managing user accounts ofvarious user devices (e.g., 210) that consume or otherwise make use ofservices of application manager 205. An example user manager 222 canassociate various modified applications 232, application data andfeedback data (e.g., 235), and application modes 240, includingapplication modes developed or modified by particular users with one ormore user accounts and user devices (e.g., 210) in a system, among otherexamples.

An application manager 205 can, in some implementations, additionallyinclude components, engines, and modules capable of providingapplication management, security, and diagnostic services to one or moreuser devices (e.g., 210) in connection with user device attempts todownload, install, activate, or otherwise use or procure variousapplications including applications provided through one or moreapplication servers (e.g., 140). For instance, in one exampleimplementation, application manager 205 can include an example behavioranalysis engine 228 adapted to analyze and identify functionality ofvarious applications made available to user devices on the system.Further, functionality of applications can be identified, for instance,by behavior analysis engine 228, that users or administrators may wishto block, limit, repair, or modify, among other examples. Accordingly,in some implementations, an example application manager 205 can includean example healing engine 225 configured to modify applications onbehalf of users to eliminate undesirable application features detected,for example, by behavior analysis engine 228 and thereby generatemodified applications 232. Modified applications 232 can, in someexamples, be specifically modified and configured based on the requests,rules, settings, and preferences of a corresponding user. Additionally,application manager 205 may include an application intelligence engine230 configured to collect application data (e.g., 235), for instance,from information servers 145 and other sources both internal andexternal application manager 205 and its client user devices (e.g.,210). An application intelligence engine 230 can be used to collectintelligence regarding one or more applications served, for instance, byapplication servers 144. The intelligence can be used in connection withservices provided by application manager 205, such as behavior analysisand assessments of applications by application manager 205, among otherexamples.

In some implementations, a user device (e.g., 210) may include one ormore processor devices 242 and one or more memory elements 245 as wellas one or more other software- and/or hardware-implemented componentsincluding, for example, a mode manager 248, settings manager 252,security tools 250, and one or more applications 255 (e.g., procuredthrough application servers 140). In one example implementation, a userdevice 210 can include a mode manager 248 that is equipped withfunctionality for defining, enforcing, and otherwise managing multipleapplication access modes 265 on the user device 210. Mode rules 270 canadditionally be managed by mode manager 248, the mode rules 270defining, for instance, particular conditions for automaticallyinitiating or enforcing various modes 265 on the user device 210.Additionally one or more settings 260 can be defined by users, forinstance, through an example settings manager 252, the settingcorresponding to and in some cases used in connection with various modes265 of the device 210, among other examples.

Turning to the example of FIG. 3, a simplified block diagram 300 isshown illustrating functionality and flows of an example applicationmanager. For example, a behavior monitor 228 can assess applications toidentify whether one or more functions and/or content of an applicationare good, bad, suspect, or of unknown quality, among other examples. Theassessment can be based on information acquired from a variety ofsources (e.g., 145), such as information servers, user feedback, andother sources. In instances where “bad” application functionality and/orcontent is identified an application healing engine 225 can be engagedto modify the application and remediate the identified undesirablefunctionality to generate a modified application file 232 correspondingto a healed version of the application. Further, suspect or unknownapplications can be designated, for instance, by a mode manager 248, tobe dedicated to a particular limited access mode of the user device 210so as to, in effect, quarantine the suspect application until moreintelligence is acquired regarding the application's functionality. Ininstances where it is determined that an application satisfies rules,requirements, or preferences of a user, network, administrator, etc.,the application may instead be allowed to proceed for installation on auser device. Further, applications which have been healed to generate amodified application file can allow for the modified application toproceed to the user device for installation on the device, among otherexamples.

FIG. 4 includes a block diagram 400 illustrating example principles andactivities enabled through an example application behavior analysisengine. Application binaries 405 can be accessed or received by adisassembler data/control flow analyzer 410 which, in combination withambient application knowledge 415 (e.g., collected from outsideinformation sources as well as users, reviewers, etc.) such asapplication descriptions, reviews, comments, and other structured andunstructured data, can develop a model of the application logic 420 foreach application binary 405. The disassembler and control flow analyzer410 can identify behaviors 425 of the given application based on, forexample, comparing code or application logic model with knownfunctionality defined in or identifiable from a software development kitand/or common APIs utilized by the corresponding client device operatingsystem as well as most or all applications compatible with the clientdevice. Some examples include the Google Android software developmentkit, Apple iOS software development kit, Windows software developmentkit, among other examples.

Generally, a platform software development kit (or “SDK”) can providedocumentation, header files, libraries, commands, interfaces, etc.defining and providing access to the various platform subsystemsaccessible by applications compatible with the platform. In one exampleimplementation, a platform SDK and corresponding APIs and API calls(i.e., calls to functions and routines of the API) can be represented ina model that can be used, for instance, by an application behaviorengine, to determine behavior and functionality of applicationscompatible with the platform. The semantics of commonly used APIs isrepresented in a program readable form along with critical informationnecessary to derive application behavior. The semantics of the platformSDK can be represented so that an example application behavior enginecan use the semantic model to understand and identify the operations andbehaviors of a given application using the API call. For example, in oneexample implementation, all of the potential API calls of the platformcan be represented, for instance through API intelligence 430, bytagging the name of each respective API call with the behavioral tagdescribing what the respective API call does on the platform as well asthe corresponding parameters of the API's operations and behaviors. Asan example, a template of such a semantic representation can be modeled,for instance, as:

  <APIName: name  <Category: read/write/process/transform/.../...>  <CategoryDetail>    <Reads: sensitivity>    <Writes: sensitivity>   <Transform: sensitivity>  <Senitivity:red:5/orange:4/yellow:3/green:1>  <Parameters: No of paramerer>  <ParameterIndex:Index>   <Type: integer/object/string/../..>  <Operation: input/output/transformative>   <return value:void/integer/object/string/>  <Dependency>   <True/False>  <Description>  <APIDescription: description of the API>   <Verbs:xxx>   <Nouns:xxx>

In the foregoing example, a “category” can designate the type of an APIcall and be used to identify the general functionality of such APIcalls, such as, that the API call reads information from a particularsubsystem, disk, etc. generates various messages, initiates variousnetwork behaviors, attempts to communicate with various outside servers,triggers particular device functions or elements (e.g., a camera, SMScontroller, etc.). “Sensitivity” can represent the respectivesensitivity of the subsystem affected or associated by the API in thecontext of the potential for malicious behavior in connection with thesubsystem, such as whether reading to a particular memory locationintroduces the potential for spying, where the subsystem potentiallypermits the introduction of malware, unauthorized tracking or datacollection, the unauthorized or undesired reading or sending of SMS oremail messages, among many other examples. Further, “dependency” canrepresent whether the output of this API can have an impact on otherparts of the program in a direct way. For instance, a sendTextMessage( )API can be identified as having no dependency where the API simply sendsan SMS message out and does not return anything, among other examples.

Other information can be used by a behavior heuristics/rule engine 435(e.g., of an example analysis engine (e.g., 228)) to determine behaviorsof an application under assessment, such as global threat intelligence(GTI) 440 aggregating intelligence from a community of sources 445,rules 450, and other information.

As noted above, an example application behavior analysis engine (e.g.,228) can possess functionality for identifying the control flows,operations, functionality, and behavior of a given application based,for instance, on a semantic representation of a standard platform SDKupon which compatible applications are based. In FIG. SA, representation500 of a simplified application control now is shown for an examplegaming application. While the functionality of the game may be in themain desirable, secure, and benign, deeper inspection of the code of thegame application binary in comparison with the semantic representationof the platform SDK as well as ambient application intelligence for thegame application, may yield identification of other functionality thatis not immediately or otherwise identifiable, understood, or appreciatedby users, such as the application sending SMS messages either with orwithout a user's explicit knowledge or permission. In another example,shown in FIG. 5B, inspection of a particular object of an applicationbinary may reveal the totality of functions and control flows of thegiven application as well as reveal dependencies between distinctprograms, program units, or applications the user may not otherwiserealize, understand, or approve of. As an example, identified behaviorheuristics can be represented externally, in some implementations, in anXML file that identifies the specific pattern of data flow and calls,from which the behavior can be identified. For instance:

  <Pattern>  < Call to API1( ): mandatory  < Call to API2( )/API3()/....: mandatory>  < Call to API5( )/API6( )/....: optional>  < Call toAPI10( ): mandatory> </Pattern>

In some implementations, based for instance on a model of the semanticrepresentation of the platform SDK, application logic can be modeled andrules can be applied to interpret the application logic and identifyinstructions and calls within a corresponding binary of the applicationthat correspond with malicious, privacy infringing, policy violating, orother undesirable behaviors. The logical model of an application'sfunctionality can include representation (e.g., 505) of the applicationlogic through data flow structures and control flow structures, amongother examples. A dataflow structure can represent the lifetime of dataobjects as they pass-through the application logic (e.g., 510) and ontoother program units (e.g., 515) including external program units. Adataflow structure (e.g., 505) can be used to identify the flow of datafrom one part of the application program as it moves and is potentiallytransformed by the application logic. For example, a dataflow model canbe used to deduce that particular data is being leaked by theapplication through an Internet communication post operation, amongother examples. Further, control flow structures can represent thecontrol flow of different function calls (e.g., 520, 525) to identify anoriginating source of an application call determined to be sensitive orundesirable. As an illustrative example, a call by the application tosend an SMS message can be traced back, for example, to a UI element ofan application interacted with by user, or even an autonomous event in abackground process of the application, among potentially many otherexamples.

Turning to the examples of FIG. 6, a simplified block diagram isillustrated representing various subsystems, devices, and functionalityaccessible by applications through one or more APIs defined in aplatform SDK, for example. In some implementations, all platformsubsystems can be categorized or assigned weights based on thesensitivity of the respective subsystem in the context of the potentialthat the subsystem could be manipulated or utilized in connection with amalicious or otherwise undesirable behavior. Such weights andsensitivities can be based on a variety of factors including, forexample, the potential for an invasion of privacy, data leaks, financialsensitivity, among other examples. These factors can also form the basisof categorizations of the various subsystems of the platform. Suchsubsystems can include, for example, contact lists, photo galleries,email clients, calendars, Internet connectivity and browsing, graphics,video functionality, cameras, audio, security tools and engines,telephony, Wi-Fi capabilities, Bluetooth capabilities, data ports,battery power, touchscreens, global positioning systems, amongpotentially many other functionalities and subsystems including futurefunctionality that can be integrated in mobile devices.

As represented in the example of FIG. 7, a rule engine of an applicationbehavior analysis engine can access rules, for instance, from a ruledatabase, including rules that have been custom defined for and/or by aparticular user or set of users according, for example, to preferencesof the users as well as policies applicable to the users (e.g., policiesof an Internet service provider, enterprise network, broadband dataprovider, etc.). The rule engine can take as a further input anapplication logic model (e.g., developed based on a semanticrepresentation of a platform SDK corresponding to the application) toassess the various operations and functionality of an application asidentified in application logic model. The rule engine can assess thevarious operations and functionality of an application according torules identified as applicable to the particular instance of anapplication, such as an instance of an application that has beenattempted to be downloaded or installed on a particular user computingdevice of a user associated with the identified rules. Applicationbehaviors can be identified by the rule engine including applicationbehaviors identified as violating one or more rules (e.g., rulesforbidding certain behaviors or actions) and prompting, in someinstances, remediation of the identified application behaviors and/orassignment of the application to one or more operation modes on thedestination user device, such as a quarantine or administrativeoperation mode, among other examples.

In some implementations, a human readable description of a behavioridentified and based on a description of API semantics can beconstructed. In one example, human relatable verbs and nouns can beassociated with template messages in the semantic representation andmapped to particular human understandable descriptions of functions andoperations available to the APIs. Further, in connection withassessments of an application according to the semantic model performed,for example, by an application behavioral analysis engine, ahuman-readable summary of the behavior analysis results can be generatedfrom the mapping and presented to a user that describes the variousfunctionality, as well as, in some implementations, the control flowdataflow of the analyzed application. Such results can make use of thehuman readable description to generate a description of thefunctionality uncovered during analysis of the application, includingfunctionality that may otherwise be invisible to or difficult to detectby the user. For example, in one implementation, the template can beutilized and populated so as to identify and describe an exampleapplication's functionality for reading SMS data from the user's device.As an illustrative example, corresponding description could be generatedsuch as: “This application reads your SMS data from SMS inbox and sendsto a web site.” Such a description could be constructed, for example, byfilling in an example template based on the semantic representation ofthe platform SDK and APIs such as: “This application <verb: reads> your<noun:SMS data> from <noun: SMS inbox> and <verb: sends> to a <noun:website>”, among other examples.

In some examples, the analyzed application behavior can reveal the useof other applications, programs, or services by the analyzedapplication. Some instances, a call to a local application, remoteservice, or other program by the analyzed application may beundesirable, for instance, when the other called application isidentified as unsecure, un-trusted, or unknown, among other examples. Inother instances, a program called or used by the analyzed applicationmay be identified as a trusted program. Accordingly, in someimplementations, an application behavior analysis engine can make useof, generate, modify, and otherwise manage whitelists and/or blackliststhat identify the status and reputations of various programs that havebeen known to or could be potentially called by various analyzedapplications. In some implementations, applications and services hostedby remote servers can additionally be identified in such whitelistsand/or blacklists by the respective URLs or other address informationcorresponding to their respective host servers, among other examples.

In some implementations, the behavioral analysis engine can identify thecontext in which a particular activity is performed, platform API isaccessed, or functionality is employed by the application underassessment. As an example, an analyzed application's attempts to accessa platform telephony subsystem can be assessed based upon the cause orcontext of the attempt. For instance, in some contexts, a particular APIcall may be perfectly acceptable while in other contexts the API callcan be undesirable. For instance identified application functionalitythat accesses the telephony subsystem in response to a user interfaceinteraction, such as a button press, may be assessed differently than anattempt by an application to access the telephony subsystem autonomouslyand not in response to a user provided directive, among other examples.

As noted above, in some implementations, rules can be defined that canbe used in the assessment of application behaviors. Such rules can berepresented and configured for use in performing heuristic analysis ofan application's logic or of a potentially malicious behavior identifiedby an application behavior analysis engine, including contexts in whichthe behavior is to be determined to be malicious. For instance, a ruleengine can apply one or more rules to an application logic model toidentify one a more potentially malicious or otherwise undesirablebehaviors present in the application. In some implementations, a rulecan be represented as:

   <Rule>  <Run><Dataflow><ReadOperation>of <red sub system>toa<WriteOperation> of <write sub system>The rules can be generic or can be specific to a particular subsystem,etc., such as a rule to detect data leak of a memory element storingpersonal contact data, among other examples. A specific applicationbehavior can be derived based on application of a single rule ormultiple rules.

In some implementations, an application behavior analysis engine can behosted on one or more server computing devices remote from the mobileuser devices for which analysis performed. In other examples, at least aportion of application behavior analysis engine can be providedalternatively or redundantly with functionality of server-sideapplication behavior analysis engine components. For instance, in oneexample implementation, a user computing device can be provided withapplication behavior analysis engine functionality allowing at least apartial or quick preliminary assessment of an application to beperformed at the user device to thereby provide a user with fastfeedback as well as assess whether an application should be quarantined,denied download or installation, and/or forwarded to a remoteapplication behavior analysis engine, such as one provided in a cloudsystem, allowing then for a more robust behavioral analysis of theapplication (that could possibly introduce increased latency into thebehavioral analysis assessment).

In some implementations, during an analysis of an application,downloading, insulation, or launching of the analyzed application may beprevented or delayed until the analysis is completed. In some instances,a user can be provided with a prompt identifying the analysis of theapplication as well as providing the user with various options fordealing with the installation, downloading, or launching of the analyzedapplication. For instance, a user may be provided with the option ofskipping the analysis, delaying installation of the analyzedapplication, assigning the analyzed application to a particular mode,among other examples. Additionally, in some implementations, a promptpresented to the user in connection with the assessment may be presentedtogether with information, such as preliminary information, gleaned fromthe behavioral analysis engine assessments and/or external intelligencerelating to the analyzed application. Such intelligence can include, forexample, intelligence gleaned by the behavioral analysis engine inprevious assessments of the analyzed application, among other examples.Indeed, in some implementations, the behavioral analysis engine canindicate to the user behaviors discovered for the application, how otherusers have responded to feedback received from the behavioral analysisengine regarding the particular analyzed application, among otherexamples.

In some implementations, behavioral analysis engine can maintainblacklists, greylists, and/or whitelists of applications known to and/orpreviously analyzed by the behavioral analysis engine. Such blacklists,greylists, and/or whitelists can be based on historical intelligencecollected from previous behavioral analyses, outside intelligence fromother sources, and other users. The behavioral analysis engine canutilize such information to perform an initial assessment of anapplication and leverage information gleaned from previous analyses.Initial filtering or feedback can thereby be provided to a user toassist the user in determining how to deal with a particular applicationas well as whether to initiate further behavioral analysis on theapplication using the behavioral analysis engine.

Behavioral analysis of applications and/or blacklists/whitelists canfurther incorporate or consider general reputation information ofdevelopers or other parties identified as responsible for variousapplications, among other examples and considerations. Rules can bedefined that consider the trustworthiness or untrustworthiness of thedeveloper, distributor, etc. of an application. For example, anapplication development score rating can be computed for a developerbased on aggregate analyses of applications of the developer by thebehavioral analysis engine. For instance, such a rating can be derivedas: AppDeveloper Rating=f(total number of apps, weighted average ofundesired behavior in apps, popularity of the app, average ratio of lowratings), among other examples. For instance, in one Illustrativeexample, a weighted average of undesired behavior can be generated for aset of applications of a developer:

Weight No of Total Behavior (out of 10) occurrence weight Contactsleakage 9 2 18 Device ID leakage 2 5 10 Message Leakage (SMS) 8 3 24Location leakage 5 4 20 Unnecessary permissions 2 1 2and average weight can be derived by Average Weight=Total Weight/Totalnumber of Apps, among other example implementations.

Outside sources, such as intelligence databases, such as a global threatintelligence (GTI) feed, can be used for identifying malicious behaviorsthat have been detected across one or more networks that may be employedby applications assessed by behavioral analysis engines. For instance,various URLs, IP addresses, phone numbers, and files can be identifiedthat have been previously determined to be associated with or used inother malicious attacks, malware, or suspect systems. Additionally, abehavioral analysis engine can interface with intelligence databases toprovide additional intelligence gleaned from the behavioral analyses ofapplications performed by the behavioral analysis engine itself, amongother examples.

Further, in some systems and platforms, applications offered by one ormore application servers or storefronts may provide users with basicdescriptions, ratings, user feedback, etc. collected for a givenapplication. Unfortunately, in many instances, such ratings, applicationdescriptions, content ratings, etc. may be provided by, manipulated by,or otherwise influenced by the application developers themselves therebydiminishing, potentially, the truthfulness or legitimacy of theinformation provided to users regarding some applications. Accordingly,in some of implementations, intelligence (e.g., behavioral descriptions)gleaned from behavioral analyses of applications performed by an examplebehavioral analysis engine may be used to supplement, correct, orotherwise modify descriptions provided to users in connection with theirbrowsing, purchasing, and downloading of applications available on aplatform. Further, in some implementations, a behavioral analysis enginecan make use of these default application descriptions, content ratings,user feedback etc. as external intelligence considered in connectionwith a behavioral analysis. In still other examples, a behavioralanalysis engine may be used to identify common behavioral traits betweenmultiple applications that can serve as the basis for categorizing theapplications according to behavior. Such categories can then be providedto users to assist users in better understanding the qualities andbehaviors, as well as potential risks, of various applications, amongother examples.

Turning to FIG. 8, a simplified schematic diagram 800 is shown of anexample flow for performing deep analysis of application behavior (e.g.,using a behavioral analysis engine) and performing application healingin an attempt to remedy those behaviors determined to be undesirable inan application while still preserving other core functionality of theapplication, in some examples. As shown, application binaries can besubmitted to a disassembler and data control flow analyzer 410 (e.g., ofa behavior analysis engine) to develop application logic models (e.g.,420) based, in some examples, additionally on ambient applicationknowledge 415, intelligence, and the like. As noted above, the model ofapplication logic 420 can be assessed based on defined rules, platformAPI intelligence, and behavioral heuristics through a behavioralheuristics/rules engine 435 to identify application behaviors of arespective application. Further, sections of code of the application canbe identified during the assessment as responsible for the exhibitedundesirable behavior. This code can be flagged for remediation.Additionally, in instances where application behaviors are identified asundesirable and are requested or dictated, by a user, administrator, orpredefined rules, to be healed, the application binaries can be furtherprocessed to remove, block, or otherwise remediate the offendingbehaviors and corresponding code to thereby generate healed versions 232of the application binaries that a user can then cause to be downloaded,installed, and executed on the user's device. Additionally, as notedabove, the global threat intelligence feed 440 or other intelligencedatabase can provide intelligence for consideration and behavioralanalyses as well as application healing. Additionally, intelligencegleaned from the behavioral analyses can be shared with outsideintelligence databases that additionally receive input, data, andintelligence from a community of users and systems 445.

Turning now to the example of FIG. 9, an additional flowchart 900 shownrepresenting decisions made in connection with the management andremediation of applications determined to include undesirable behaviorsbased on behavioral analyses of the applications. For instance, rulesand policies can be defined, for instance, by a user or system ornetwork administrator, to define how and under what conditionsapplications are to be handled that have been determined to include oneor more undesirable behaviors. Such policies can, for example, identifyparticular types of undesirable behaviors and map such behaviors topredefined courses of action, such as the healing or remediation of theapplications, blacklisting or whitelisting of the applications,quarantining of the applications, among other examples. Additionally,user inputs can drive management of an application's deployment on auser computing device. Such inputs can be received in connection withprompts presented to the user and can include, for example, requests toremediate one or more identified undesirable behaviors, instructions toassign the analyzed application to a particular operation mode orquarantine area, among other examples.

As noted above, static healing and personalization of applicationbehavior can be performed by a healing engine allowing the code of theapplication to be modified and generate a “safe” version of theapplication that allows the user to retain safe or legitimatefunctionality of the application while removing undesirable behaviors.Such healing can in some cases be personalized or customized toparticularly-defined policies driving the healing, thereby allowing auser, service provider, device manufacturer, etc. to control andpersonalize the functionality of applications to be installed oncorresponding user devices. In FIG. 10, simplified b diagram 1000 isillustrated showing the flow of an example healing of an originalapplication 1005. Upon identifying 1010 undesirable behaviors andoffending sections of the code of the application binary, a healingengine can be provided for identifying, removing, replacing, orblocking, the offending code and corresponding behaviors in order togenerate a modified application binary 1015. As an example, a healingengine 228 may include logic for modifying an application by removing orblocking various types of undesired behaviors such as, in this example,unauthorized reads or accesses of SMS functionality by removing theoffending instructions discovered in the original application binary. Inother instances, such as shown in this example, a healing engine maymodify the offending code, such as by rewriting the code to redirect anAPI call to a trusted system, destination, address, etc. A healingengine 228 can modify the original code with minimal changes so as toavoid affecting the core desired functionality of the application.Further, healing policies can identify the patterns that are consideredfor identifying application code for healing. This can be represented,for example, in an XML file that identifies the heuristic pattern ofcode corresponding to an offending behavior. Each type of defined oridentified pattern of code can be healed by a specific healing method,such as according to corresponding policies. Such methods can beidentified and defined in such a way that the healing does not impactthe rest of the application's functionality.

A variety of healing methods can be employed by an application healerengine. For instance, a particular offending line of code functionalitycan be identified as a final or leaf node in a control chain. In suchinstances, the offending code may be determined to be able to besuppressed or removed without affecting other dependencies in theapplication, among other examples. In another example, if a removal of aparticular API call is determined to likely have no impact onsurrounding code, the removal healing method can be applied. The natureand character of APIs can be learned, for example, from the semanticplatform SDK representation, among other examples. In other instances,the offending behavior can be from one or more sections of code and mayresult in multiple methods of healing applied to remediate the behavior,such as by replacing the data in a register to alter the behavior of theAPI or redirecting of the API call to a new version of the API with sameinterface by replacing the offending API code with the new API code,among other examples. In instances where a new version of an API isintroduced, the new API may, for example, do nothing and set theregister status so as not to impact other parts of the program, processthe inputs in a different way to avoid the undesired behavior, or dopre-processing and/or post-processing of the input/output parameter andcall the original API, among other example techniques that resolve theundesirable behavior.

Turning to FIG. 11, a simplified block diagram is illustrated showingthe identification of code relating to particular undesirable behaviors.For instance, sections 1 a and 1 b of application code can be identifiedas corresponding to a first, detected, undesirable behavior and sections2 a and 2 b can be identified as corresponding to a second undesirablebehavior of the application. Accordingly, healing the application caninclude modifying or replacing the identified offending sections of codewith code that modifies or suppresses the undesirable behaviors.Further, healing policies can be identified corresponding to theidentified code or API calls to identify healing techniques formodifying the offended code and remediating the undesired behaviors.

In FIGS. 12A-12E, additional examples are illustrated of the detectionof undesirable behaviors as well as the remediation of the undesirablebehaviors. For example, in FIG. 12A, an example code fragment allowingan application to send latitude and longitude information to an outsideserver is shown as having been processed to populate an API template,for instance, utilizing a behavior analysis engine. As shown in FIG.12B, portions of the application code can be identified that correspondto the behavior of collecting geo-positional data and sending thegeo-positional data to the outside server. In accordance with oneexample, the offending lines of code can be replaced, for example withcode that masks or redirects the sending of the geo-positional data toprevent the application from tracking user location, among otherexamples. In another example, illustrated in FIG. 12C, a control flowcan be identified within an application along with correspondingapplication code. As shown in the examples of FIGS. 12D-12E, remediationof a particular undesirable behavior can include deletion of anoffending line of code, among other examples.

FIG. 13 illustrates an example flow 1300 in connection with remediationof one or more detected undesirable behaviors of an application. Forinstance, the connection with the dynamic personalization of anapplication's behavior for particular user, the composite behaviors ofthe application and corresponding code segments can be identified. Auser interface can be presented in connection with the healing orcustomization of the application allowing the user to select particularidentified behaviors for remediation or modifications. In one exampleimplementation, the user interface can be provided in connection with anapplication healing engine with the user inputs directing how (e.g.,which identified behaviors) the application healing engine is to modifythe application. In another example, application healing engine caninsert one or more user interface controls into the original binary ofthe application allowing the user at launch of the modified applicationto dynamically enable, disable, or otherwise remediate or customize thebehavior of the application. For instance, based on the selections ofthe user, an original section of the code corresponding to an acceptedbehavior can be utilized in lieu of a healed version of the same code,among other examples. Effectively, each of the segments of the codewhere behavior is demonstrated can be selectively turned off or on basedon the user preferences and inputs. Further, the user interface canprovide a user with the option of saving the settings of an applicationso that the selection of a particular subset of application behaviorspersists and is available the next time the application is launched onthe user's device.

In some implementations, functionality can be provided to define,enable, and employ defined usage modes on the user devices.Traditionally, user devices, such as smart phones and tablet computers,among other examples, are designed to support a single user andapplication profile. However, a single operation profile and mode maynot be appropriate for all of the actual users of the device or thesituations in which the device is used. For instance, a user may desireto loan their device to a friend for some short period of time, butwould like to nonetheless retain control of the access to some of thesensitive applications and data on the device, email applications,contacts, calendars, messaging functionality, etc. In other instances,the user may desire to allow a child to temporarily use the device, forexample, to play game, but would prefer for other applications (e.g.,web browsers) and access to certain device settings and data to beblocked from the child. Additionally, users may desire to control usageof some subset of the applications on the device to specific times,locations, and situations. For instance, games and social networkingapplications may be desired to be disabled during school hours, amongother examples.

FIG. 14A illustrates a simplified block diagram 1400 a of an exampleimplementation of a mode manager. For instance, various modes may bedefined based on intelligence gleaned from the user device as well asoutside services. A user may define one or more modes through a userinterface and a mode manager, for instance, on the device may manageaccess to the various modes, for example, using dedicated credentialsassigned to each of the modes. Additionally, as noted above, anapplication monitoring service or application behavioral analysis enginemay recommend particular applications for a quarantine or high-securitymode available on the user device. Accordingly, a user may define suchmodes to restrict access to potentially risky or currently analyzedapplications to administrative, adult, or other trusted users, amongother examples.

FIG. 14B illustrates another simplified block diagram 1400 billustrating principles of an application mode manager. An applicationmode manager 248, in some implementations, may include various modulesand functionality such as a mode setup manager 1405, lock service 1410,lock manager 1415, credential manager 1420, application access manager1425, application protection service 1430, password engine 1435, amongother examples. For instance, in the illustrated example, the user withadministrative privileges can set up passwords or PINs and assign thesecredentials to modes defined by the user, for instance, using a modesetup manager. An access manager can utilize a credential manager toverify whether valid credentials have been received that allow a currentuser of the device to access one of a set of modes defined for thedevice. In the event that incorrect credentials are entered, a lockmanager can invoke a lock service to lock out the current user from oneor more applications by assigning the user to a restricted mode orlocking out the user altogether.

In some implementations, a device mode can be composed of an exclusionlist or inclusion list. Device modes can be defined as respective setsof applications that are either allowed or somehow protected in thatmode, in the sense their usage is prohibited or limited. In someinstances, an exclusion list can be defined for a mode that indicates aparticular subset of the applications and/or subsystems of a device thatare accessible under the corresponding mode (i.e., with the remainingapplications protected or locked in that mode). For instance, a mode canbe defined such as according to: <ModeName, inclusion/Exclusion, AccessPIN, App1, App2, App3 . . . App N>. In some instances, each device modecan be protected and associated with a particular password. The mastermode can be defined that allows access to the entirety of the device'sfunctionality and applications. Accordingly, a master password can beprovided that enables access to the master mode. Within the master mode,the user may be provided with access to a management console formanaging the set of modes available or defined at the device.Accordingly the user may edit or define modes through the managementconsole, as well as activate or delete predefined modes. An examplemanagement console can allow a user to select, from a listing ofapplications, those applications the user wishes to designate asprotected or accessible in any given mode. In some cases, a singleapplication can be allowed or protected under multiple different modes.

In some implementations, mode passwords may be stored in encryptedmemory. For instance, the password of each mode can be encrypted using akey generated by the same password. A stored, encrypted password canthen be validated by decrypting the password with a key generated fromthe password entered by the user. The decrypted data can then becompared with the user-entered password. Based on the password providedby user, a corresponding mode can be identified and authenticated toallow access to the mode by the user. In some implementations, the usermay manually lock the device or the device may lock itself, forinstance, after a prolonged period of inactivity. When attempting tounlock the device or wake up the device a user may be again presentedwith a login prompt requesting a password of one of the modes availableand defined for the device.

In some implementations, modes can be hierarchical. For instance, a userlogged into a higher level mode (i.e., a mode providing a relativelygreater level of access), may be able to freely move to another modewithout providing credentials for that lower-level mode. On the otherhand, a user who has been authenticated to a lower level mode may beforced to enter additional credentials when attempting to access anothermode at a higher level in the hierarchy than the lower-level mode towhich the user was previously authenticated. For example, in oneinstance, four device modes can be defined where:

Mode1 is admin level mode;

Mode 2 guest level mode;

Mode 3 is guest level mode; and

Mode 4 is low privilege mode

and the hierarchy is defined as: Mode1>(Mode2 and Mode 3)>Mode 4, whereMode2 is the same level as Mode3, among other example implementations.

In some implementations, configuration of the device can be altered,customized, or at least partially restricted when certain modes areactive. For example, a particular mode can activate or deactivate GPSfunctionality, data access, telephony, as well as certain applications.Further, in some examples, device modes can be provided that secure dataof particular applications when mode. For instance, once a new mode hasbeen created and assigned a corresponding access level to set ofapplications, the data of these applications may be protected byencryption through a separate encryption key. This can be implementedfor example by using an encrypting file system for encrypting files andfolders, among other examples.

In some implementations, the executable code of applications can besecured to protect against applications being used in modes thatdisallow access and/or use to one or more of the behaviors or featuresof the application. For instance, in one implementation, the applicationexecutable can be stored in encrypted secondary storage. An operatingsystem loader of the user device can gain conditional unencrypted accessto the executable code, in some examples, only if the application isfound in an allowed application list for the active device mode in whichaccess to the application is attempted, among other potentialimplementations.

In some examples, defining multiple device modes for a user device canfurther result in the provision of multiple unique home screens to bepresented in each of the corresponding modes. As a result, in suchimplementations, the appearance of a given home screen can indicate to auser the mode that is active on the device as well as access privilegesavailable in that mode. In some instances, home screens can includeicons of applications that are available within that corresponding mode,hiding or obscuring the icons of other applications that are protectedwithin that mode, among other examples.

Further, in some instances, device modes can be created automatically,for instance, based on identified behaviors and security profiles ofapplications that are detected or loaded on the user device. Forinstance, a mode manager can make use of behavioral analyses performed,for example, by an example application behavioral analysis engine, toidentify applications that exhibit a common category of behaviors orcategory of security profiles. For instance, applications identified aspermitting access to online resources may be grouped and assigneddynamically to one or more modes that have been defined as allowing suchaccess. Other modes, such as modes dedicated for underage users, may bedenied access to applications that allow users to access the Internet,among other examples. Other example categories may include applicationsthat enable telephony or mobile messaging functionality, applicationsthat make use of subsystems that utilize sensitive data, collectpotentially private information (e.g., cameras, voice recorders, GPSsystems, etc.), and other examples. In some implementations, ambientintelligence relating to an application, such as an age rating (e.g.,7+, 12+, 18+ years, etc.), user reviews, or other information may beused to categorize applications and group them in various modes. Forexample, a description of an application may include an age or maturityrating as well as reasons for the maturity rating. Accordingly, in oneexample, one or more modes may be defined, for example, that blockaccess by child users to applications with higher maturity ratings,among other examples.

Other global or distributed intelligence can also be used to developinformation for a given application, such as illustrated in thesimplified block diagram 1900 of FIG. 19. For instance, applicationinformation can be constructed from security information regardingbehaviors of an application from global threat intelligence 440,publisher/developer reputation information 1905, app store feedback andreviews 1910, behavior analysis results 1915, among other examples. Suchinformation (e.g., 440, 1905, 1910, etc.) can be used in combinationwith behavioral assessments 1915 of the applications (e.g., whether anapplication potentially leaks data, provides location information,enables SMS messaging, etc.) to assign certain applications toparticular device modes, such as quarantine or administrative modes,among other examples. A user may further designate custom categories orbehaviors or select pre-defined categories or behaviors as the basis forassignments of applications to respective modes rather than individuallyselecting the applications for inclusion in one or more modes on al acarte basis, among other examples.

Turning to the example of FIG. 15A, an example algorithm is representedfor the storing of password information associated with a particularmode. FIG. 15B represents an example algorithm for validating a passwordand identifying a mode to activate that corresponds to the enteredpassword. It should be appreciated that the algorithms of FIGS. 15A-15Bare non-limiting examples presented merely for purposes of illustrationand that other alternative algorithms and implementations can beutilized in other instances.

Turning to the example of FIG. 16, in some implementations, modesdefined by a given user may be provided, for instance, to an applicationmanagement service, cloud service or other service (e.g., 1600) thatallows one or more modes, as well as rules associated with the modes, tobe aggregated and shared with other users. Additionally, shared devicemodes maintained by a mode sharing service 1600 can be browsed andselected for download and utilization on user devices 110, 120, allowinga user to provision their own device with modes created by other usersand shared using the mode sharing service. Further, the user canprovision the shared mode, in some examples, by downloading andinstalling a definition of the shared mode from the mode sharing serviceand assigning a unique password to the newly installed mode. In stillother examples, mode configurations can be shared directly betweendevices, with one device obtaining a new mode from another devicesharing the mode, for instance, through wireless peer-to-peertechnologies like Bluetooth, near field communications (NFC), WiFi, andothers.

In some implementations, such as shown in the example of FIG. 17, modescan be activated automatically based on context information detected,for example, by the device itself. A user, in some examples, canconfigure (e.g., on the management console), rules for automaticallyactivating particular modes. For instance, a particular mode can beactivated automatically in response to the detection of a specificcontext at the user device. Such contexts can include, for example,detecting the location or proximity of the device within a definedgeo-fence, detecting that the device is in proximity of other devices,detecting the device in range of particular data networks, detecting auser of the device (e.g., based on user biometric information collectedby the device), a detected time of day, device battery status, usageactivity (e.g., to guard against particular users spending too much timeon the device, etc.), whether the device is traveling or in motion(e.g., as detected through GPS functionality, accelerometers, or otherfunctionality on the device), among potentially many other examples.

Turning now to the example of FIG. 18, in some implementations, modescan be provisioned and configured through a remote service, such as acloud service, allowing a user to activate/deactivate or define a moderemotely. Using such a service, a user can create a mode remotely (e.g.,using a computer other than the target mobile user device) and provisionone or more modes to the target user device and also activate anddeactivate the mode on the user device from a remote location. Further,an administrator can also use the service to provision such modes onmobile user devices as well as define rules and contexts forautomatically activating, applying, or deactivating a given mode, amongother examples.

FIGS. 20A-20D illustrate example screenshots of user interfaces showingparticular features of some example implementations of mode managementon a mobile user device. For instance, screenshot in FIG. 20Aillustrates a user interface for defining a new mode and mode password.A similar user interface can be provided to allow a user to select andactivate one of multiple available modes on the device and/or providecredentials for the selected mode. In some implementations, a userdevice may include native login credentials or a native login manager. Amode manager may be implemented as an application itself that overridesa native login manager and replaces a native login screen with themode-specific login prompts (e.g., that allow the multi-modefunctionality of the user device). In some instances, a user may not beable to visually distinguish that a user device is provisioned withmultiple modes, with the login screen capable of accepting one of aplurality of different login codes, each login code corresponding to asupported mode (including hidden modes) provisioned on the user device.

The screenshot of FIG. 208 illustrates a view of a home screen for aparticular mode. As shown in this example, a set of restrictedapplications can be designated that can only be accessed by providingcredentials to and activating a higher level mode (e.g., that permitsaccess of the restricted applications). Further, a My Apps folder canprovide access to those applications that have been enabled in a currentactive mode. Screenshot of FIG. 20C provides another view of an exampleadministrative screen that permits users to activate, edit, or createnew modes. Additionally, example screenshot of FIG. 20D illustrates auser interface that can be provided in some implementations of a modemanager allowing a user to designate from a list of applications on thedevice which applications are to be included or protected in a givenmode, and so on. It should be appreciated that the foregoing examplesare provided merely for the sake of illustrating certain principles andshould not be interpreted as limiting examples. Indeed, a variety ofdifferent implementations, user interfaces, program architectures,operating systems, SDK platforms, and method sequences can besubstituted for those examples described above without diverting fromthe general principles illustrated and described in this Specification.

FIGS. 21A-21C are flowcharts 2100 a-c illustrating example techniques inthe management of applications on mobile user computing devices. Forinstance, in the example of FIG. 21A, code of a particular applicationcan be analyzed 2105, for instance, against a semantic representation ofa platform, such as a representation of a platform SDK and/or APIs. Aset of behaviors of the particular application can be identified 2110.At least one undesirable behavior in the set of behaviors can beidentified 2115, for instance, based on the user selection of one of theidentified set of behaviors or automatically according to rules and/orpolicies defined (e.g., by a user or administrator) for applications tobe downloaded, installed, launched, or otherwise used at a particularmobile computing device.

In the example of FIG. 218, a behavior can be identified 2120 and a setof behaviors detected for a particular application (e.g., according tothe principles of the example of FIG. 21A). A section of code of theparticular application can then be identified 2125 corresponding to theidentified behavior. A remediation action can be performed 2130 on theidentified section of code to automatically remediate the behavior, forinstance, in response to an identification that the identified behavioris an undesirable behavior, etc. The remediation action can result inthe dynamic generation of a “healed” version of the particularapplication that retains at least a portion of its originalfunctionality, with the undesired functionality being blocked orstripped from the healed version.

In the example of FIG. 21C, a particular one of a plurality of modes canbe activated 2140. The modes can be defined for a particular usercomputing device and dictate what subset of the functionality of thecomputing device and its software may be accessible to a particular userhaving credentials for accessing a respective mode in the plurality ofmodes. Access can be restricted 2145 to one or more applicationsinstalled on the user computing device according to the activation 2140of the particular mode. In addition, in some implementations, activationof the particular mode can result in a restricted or alternateconfiguration of the computing device to be applied that thereby limitsa user's access to one or more subsystems and functionality, includinghardware functionality, and settings and data of the user computingdevice, among other examples.

Although this disclosure has been described in terms of certainimplementations and generally associated methods, alterations andpermutations of these implementations and methods will be apparent tothose skilled in the art. For example, the actions described herein canbe performed in a different order than as described and still achievethe desirable results. As one example, the processes depicted in theaccompanying figures do not necessarily require the particular ordershown, or sequential order, to achieve the desired results. In certainimplementations, multitasking and parallel processing may beadvantageous. Additionally, diverse user interface layouts andfunctionality can be supported. Other variations are within the scope ofthe following claims.

Embodiments of the subject matter and the operations described in thisspecification can be implemented in digital electronic circuitry, or incomputer software, firmware, or hardware, including the structuresdisclosed in this specification and their structural equivalents, or incombinations of one or more of them. Embodiments of the subject matterdescribed in this specification can be implemented as one or morecomputer programs, i.e., one or more modules of computer programinstructions, encoded on computer storage medium for execution by, or tocontrol the operation of, data processing apparatus. Alternatively or inaddition, the program instructions can be encoded on an artificiallygenerated propagated signal, e.g., a machine-generated electrical,optical, or electromagnetic signal that is generated to encodeinformation for transmission to suitable receiver apparatus forexecution by a data processing apparatus. A computer storage medium canbe, or be included in, a computer-readable storage device, acomputer-readable storage substrate, a random or serial access memoryarray or device, or a combination of one or more of them. Moreover,while a computer storage medium is not a propagated signal per se, acomputer storage medium can be a source or destination of computerprogram instructions encoded in an artificially generated propagatedsignal. The computer storage medium can also be, or be included in, oneor more separate physical components or media (e.g., multiple CDs,disks, or other storage devices), including a distributed softwareenvironment or cloud computing environment.

Networks, including core and access networks, including wireless accessnetworks, can include one or more network elements. “Network elements”can encompass various types of routers, switches, gateways, bridges,load balancers, firewalls, servers, inline service nodes, proxies,processors, modules, or any other suitable device, component, element,or object operable to exchange information in a network environment. Anetwork element may include appropriate processors, memory elements,hardware and/or software to support (or otherwise execute) theactivities associated with using a processor for screen managementfunctionalities, as outlined herein. Moreover, the network element mayinclude any suitable components, modules, interfaces, or objects thatfacilitate the operations thereof. This may be inclusive of appropriatealgorithms and communication protocols that allow for the effectiveexchange of data or information.

The operations described in this specification can be implemented asoperations performed by a data processing apparatus on data stored onone or more computer-readable storage devices or received from othersources. The terms “data processing apparatus,” “processor,” “processingdevice,” and “computing device” can encompass all kinds of apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, a system on a chip, or multipleones, or combinations, of the foregoing. The apparatus can includegeneral or special purpose logic circuitry, e.g., a central processingunit (CPU), a blade, an application specific integrated circuit (ASIC),or a field-programmable gate array (FPGA), among other suitable options.While some processors and computing devices have been described and/orillustrated as a single processor, multiple processors may be usedaccording to the particular needs of the associated server. Referencesto a single processor are meant to include multiple processors whereapplicable. Generally, the processor executes instructions andmanipulates data to perform certain operations. An apparatus can alsoinclude, in addition to hardware, code that creates an executionenvironment for the computer program in question, e.g., code thatconstitutes processor firmware, a protocol stack, a database managementsystem, an operating system, a cross-platform runtime environment, avirtual machine, or a combination of one or more of them. The apparatusand execution environment can realize various different computing modelinfrastructures, such as web services, distributed computing and gridcomputing infrastructures.

A computer program (also known as a program, software, softwareapplication, script, module, (software) tools, (software) engines, orcode) can be written in any form of programming language, includingcompiled or interpreted languages, declarative or procedural languages,and it can be deployed in any form, including as a standalone program oras a module, component, subroutine, object, or other unit suitable foruse in a computing environment. For instance, a computer program mayinclude computer-readable instructions, firmware, wired or programmedhardware, or any combination thereof on a tangible medium operable whenexecuted to perform at least the processes and operations describedherein. A computer program may, but need not, correspond to a file in afile system. A program can be stored in a portion of a file that holdsother programs or data (e.g., one or more scripts stored in a markuplanguage document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

Programs can be implemented as individual modules that implement thevarious features and functionality through various objects, methods, orother processes, or may instead include a number of sub-modules, thirdparty services, components, libraries, and such, as appropriate.Conversely, the features and functionality of various components can becombined into single components as appropriate. In certain cases,programs and software systems may be implemented as a composite hostedapplication. For example, portions of the composite application may beimplemented as Enterprise Java Beans (EJBs) or design-time componentsmay have the ability to generate run-time implementations into differentplatforms, such as J2EE (Java 2 Platform, Enterprise Edition), ABAP(Advanced Business Application Programming) objects, or Microsoft's.NET, among others. Additionally, applications may represent web-basedapplications accessed and executed via a network (e.g., through theInternet). Further, one or more processes associated with a particularhosted application or service may be stored, referenced, or executedremotely. For example, a portion of a particular hosted application orservice may be a web service associated with the application that isremotely called, while another portion of the hosted application may bean interface object or agent bundled for processing at a remote client.Moreover, any or all of the hosted applications and software service maybe a child or sub-module of another software module or enterpriseapplication (not illustrated) without departing from the scope of thisdisclosure. Still further, portions of a hosted application can beexecuted by a user working directly at a server hosting the application,as well as remotely at a client.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform actions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random access memory or both. The essential elements of a computer area processor for performing actions in accordance with instructions andone or more memory devices for storing instructions and data. Generally,a computer will also include, or be operatively coupled to receive datafrom or transfer data to, or both, one or more mass storage devices forstoring data, e.g., magnetic, magneto optical disks, or optical disks.However, a computer need not have such devices. Moreover, a computer canbe embedded in another device, e.g., a mobile telephone, a personaldigital assistant (PDA), tablet computer, a mobile audio or videoplayer, a game console, a Global Positioning System (GPS) receiver, or aportable storage device (e.g., a universal serial bus (USB) flashdrive), to name just a few. Devices suitable for storing computerprogram instructions and data include all forms of non-volatile memory,media and memory devices, including by way of example semiconductormemory devices, e.g., EPROM, EEPROM, and flash memory devices; magneticdisks, e.g., internal hard disks or removable disks; magneto opticaldisks; and CD ROM and DVD-ROM disks. The processor and the memory can besupplemented by, or incorporated in, special purpose logic circuitry.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a computerhaving a display device, e.g., a CRT (cathode ray tube) or LCD (liquidcrystal display) monitor, for displaying information to the user and akeyboard and a pointing device, e.g., a mouse or a trackball, by whichthe user can provide input to the computer. Other kinds of devices canbe used to provide for interaction with a user as well; for example,feedback provided to the user can be any form of sensory feedback, e.g.,visual feedback, auditory feedback, or tactile feedback; and input fromthe user can be received in any form, including acoustic, speech, ortactile input. In addition, a computer can interact with a user bysending documents to and receiving documents from a device, includingremote devices, which are used by the user.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back end component,e.g., as a data server, or that includes a middleware component, e.g.,an application server, or that includes a front end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back end, middleware, or front end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include any internal or external network,networks, sub-network, or combination thereof operable to facilitatecommunications between various computing components in a system. Anetwork may communicate, for example, Internet Protocol (IP) packets,Frame Relay frames, Asynchronous Transfer Mode (ATM) cells, voice,video, data, and other suitable information between network addresses.The network may also include one or more local area networks (LANs),radio access networks (RANs), metropolitan area networks (MANs), widearea networks (WANs), all or a portion of the Internet, peer-to-peernetworks (e.g., ad hoc peer-to-peer networks), and/or any othercommunication system or systems at one or more locations.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. In someembodiments, a server transmits data (e.g., an HTML page) to a clientdevice (e.g., for purposes of displaying data to and receiving userinput from a user interacting with the client device). Data generated atthe client device (e.g., a result of the user interaction) can bereceived from the client device at the server.

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of anyinventions or of what may be claimed, but rather as descriptions offeatures specific to particular embodiments of particular inventions.Certain features that are described in this specification in the contextof separate embodiments can also be implemented in combination in asingle embodiment. Conversely, various features that are described inthe context of a single embodiment can also be implemented in multipleembodiments separately or in any suitable subcombination. Moreover,although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination.

The following examples pertain to embodiments in accordance with thisSpecification. One or more embodiments may provide an apparatus, asystem, a machine readable medium, and a method to analyze code of aparticular application against a semantic model of a softwaredevelopment kit of a particular platform, identify, based on theanalysis of the code, a set of behaviors of the particular application,and identify that one or more of the set of behaviors are undesiredbehaviors. The semantic model can associate potential applicationbehaviors with one or more of APIs of the particular platform.

In one example, identifying that one or more of the set of behaviors areundesired behaviors includes determining that the one or more behaviorsviolate one or more rules. The rules can be associated with a particularuser.

In one example, a user input identifies one or more of the set ofbehaviors as undesirable. The user input can be received in connectionwith a user interface displaying human readable descriptions of theidentified set of behaviors.

In one example, code of the particular application can be disassembledinto a control flow and a model of application logic for the particularapplication can be generated based at least in part on the semanticmodel. The model of application logic can be further based, at least inpart, on ambient application knowledge.

In one example, a remediation action can be performed based on theidentification that one or more of the set of behaviors are undesiredbehaviors.

In one example, the code of the particular application is analyzed inconnection with an attempt to implement the particular application on aparticular user device.

One or more embodiments may provide an apparatus, a system, a machinereadable medium, and a method to identify a particular behavior in a setof behaviors detected as included in a particular application, identifya section of code of the particular application corresponding to theparticular behavior, and perform a remediation action on the section ofcode to remediate the particular behavior and generate a healed versionof the particular application.

In one example, the remediation action preserves other behaviors of theparticular application other than the particular behavior.

In one example, the remediation action includes deleting the section ofcode.

In one example, the remediation action includes rewriting the section ofcode.

In one example, the remediation action includes adding additional codeto the application to nullify the particular behavior.

In one example, the remediation action is identified from a policyidentifying a remediation pattern determined to be applicable toremedying the particular behavior.

In one example, the remediation action includes inserting applicationlogic allowing a user to selectively enable a healed version of theparticular behavior at launch of the healed application on a userdevice. The user can be further allowed to selectively enable anunhealed version of the particular behavior in lieu of the healedversion.

In one example, the set of behaviors of the particular application canbe detected through an analysis of code of the particular application.

In one example, the remediation action is triggered by a user request.

One or more embodiments may provide an apparatus, a system, a machinereadable medium, and a method to activate a particular one of aplurality of modes defined for a particular user device, and restrictaccess to one or more applications installed on the particular userdevice in accordance with the activated particular mode. The restrictedapplications can be accessible when another one of the plurality ofmodes is activated.

In one example, the particular mode is activated in response to aparticular passcode entered by a user of the particular user device,where each of the plurality of modes is associated with a correspondingpasscode. Activation of the particular mode can include identifying theparticular mode from the plurality of modes based on the entry of theparticular passcode, and authenticating access to the particular modebased on the entry of the particular passcode.

In one example, one or more of the plurality of modes are user-definedmodes.

In one example, an alternate device configuration can be applied to theparticular user device based on activation of the particular mode. Thealternate device configuration can restrict access to one or moresubsystems of the particular user device.

In one example, one of the plurality of modes is an administrative modesallowing for modification of the plurality of modes.

In one example, at least one of the plurality of modes is an instance ofa mode downloadable from a mode sharing service remote from theparticular user device.

In one example, the particular mode is activated automatically based atleast in part on the detection of a particular context usingfunctionality of the particular user device.

In one example, at least a particular one of the applications isrestricted based on a defined rule for the particular mode.

In one example, the defined rule pertains to detected behavior of theparticular application.

In one example, the plurality of modes includes a mode designated as aquarantine mode for application awaiting behavioral analysis orremediation.

In one example, the particular mode is activated in response to a usercommand received at a device remote from the particular user device.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems cangenerally be integrated together in a single software product orpackaged into multiple software products.

Thus, particular embodiments of the subject matter have been described.Other embodiments are within the scope of the following claims. In somecases, the actions recited in the claims can be performed in a differentorder and still achieve desirable results. In addition, the processesdepicted in the accompanying figures do not necessarily require theparticular order shown, or sequential order, to achieve desirableresults.

1-74. (canceled)
 75. At least one machine accessible storage mediumhaving instructions stored thereon, the instructions when executed on amachine, cause the machine to: analyze code of a particular applicationagainst a semantic model of a software development kit of a particularplatform, wherein the semantic model associates a plurality ofapplication behaviors with respective application programming interface(API) calls of the particular platform; identify, based on the analysisof the code, a set of behaviors of the particular application; andidentify that a particular one of the set of behaviors is an undesiredbehavior.
 76. The storage medium of claim 75, wherein identifying thatthe particular behavior is an undesired behavior includes determiningthat the one or more behaviors violate one or more rules.
 77. Thestorage medium of claim 76, wherein the rules are associated with aparticular user.
 78. The storage medium of claim 77, wherein at least aportion of the rules include rules defined by the particular user. 79.The storage medium of claim 76, wherein the rules are associated with anetwork service provider.
 80. The storage medium of claim 75, wherein auser input identifies that the particular behavior is undesired.
 81. Thestorage medium of claim 80, wherein the user input is received inconnection with a user interface displaying human readable descriptionsof the identified set of behaviors.
 82. The storage medium of claim 81,wherein the human readable description is generated using a template forgenerating the description and the semantic model.
 83. The storagemedium of claim 75, wherein the particular user device is one of a smartphone and a tablet computing device.
 84. A method comprising: analyzingcode of a particular application against a semantic model of a softwaredevelopment kit of a particular platform, the semantic model associatinga plurality of application behaviors with respective applicationprogramming interface (API) calls of the particular platform;identifying, based on the analysis of the code, a set of behaviors ofthe particular application; and identifying that a particular one of theset of behaviors is an undesired behavior.
 85. The method of claim 84,further comprising disassembling code of the particular application intoa control flow and generating a model of application logic for theparticular application based at least in part on the semantic model. 86.The method of claim 85, wherein the model of application logic isfurther based, at least in part, on ambient application knowledge. 87.The method of claim 84, further comprising performing a remediationaction based on the identification that one or more of the set ofbehaviors are undesired behaviors.
 88. The method of claim 84, whereinthe code of the particular application is analyzed in connection with anattempt to implement the particular application on a particular userdevice.
 89. The method of claim 88, further comprising restrictingimplementation of the particular application on the particular userdevice based on identifying that one or more of the set of behaviors areundesired behaviors.
 90. The method of claim 89, wherein restrictingimplementation includes blocking installation of the particularapplication on the particular user device.
 91. The method of claim 89,wherein restricting implementation includes assigning the particularapplication to a device mode that is to limit access to the particularapplication.
 92. The method of claim 89, further comprising modifyingcode of the particular application to remediate the undesired behavior.93. A system comprising: at least one processor device; at least onememory element; and an application behavioral analysis engine, adaptedwhen executed by the at least one processor device to: analyze code of aparticular application against a semantic model of a softwaredevelopment kit of a particular platform, wherein the semantic modelassociates a plurality of application behaviors with respectiveapplication programming interface (API) calls of the particularplatform; identify, based on the analysis of the code, a set ofbehaviors of the particular application; and identify that a particularone of the set of behaviors is an undesired behavior.
 94. The system ofclaim 93, further comprising an application healer engine to: identify asection of code of the particular application corresponding to theparticular behavior; and perform a remediation action on the section ofcode to remediate the particular behavior and generate a healed versionof the particular application.
 95. The system of claim 93, furthercomprising a mode manager to: activate a particular one of a pluralityof modes defined for a user device; and restrict access to theparticular application in accordance with the activated particular mode,wherein the particular application is made accessible when another oneof the plurality of modes is activated.
 96. The system of claim 93,further comprising a user device, wherein the application behavioralanalysis engine is to communicate results of the analysis of the code tothe user device based on an attempt by the user device to install theparticular application on the user device.
 97. A system comprising:means for analyzing code of a particular application against a semanticmodel of a software development kit of a particular platform, thesemantic model associating a plurality of application behaviors withrespective application programming interface (API) calls of theparticular platform; means for identifying, based on the analysis of thecode, a set of behaviors of the particular application; and means foridentifying that a particular one of the set of behaviors is anundesired behavior.